Contrast Ultrasonography: Necessity of Linear Data Processing for the Quantification of Tumor Vascularization

Purpose: This study is intended to compare the value of uncompressed ultrasonic data, obtained after linear power detection of the ultrasonic radiofrequencies that we call linear data, with usual compressed video data for the quantification of tumor perfusion, particularly for monitoring antivascular therapy. Materials and Methods: To form a clinically useful ultrasonic image, the detected power of the received signals (linear data) is compressed in a quasi-logarithmic fashion in order to match the limited dynamic range of the video monitor. The resulting reduced range of signals from an injected contrast agent may limit the sensitivity to changes in the time-intensity curves. Following a theoretical evaluation of the effects of compression on time-intensity curves and as an in vivo example, we measured at different times the effects of an antivascular drug administered to mice bearing melanoma tumors. The mean time-intensity curves within the tumors after bolus injection of a contrast agent were determined using both linear and video data. Linearized data was recovered using the inverse of the true scanner's compression law, which was experimentally determined. Three features were extracted from the time-intensity curves: peak intensity (PI), time to peak intensity (TPI) and area under the curve in the wash-in phase (AUC(wash-in)). When contrast reached its maximum value, the coefficient of variation reflecting the heterogeneity of the intensity of contrast uptake within the tumor, was computed using both data sets. Results: TPI was found to be similar with either data set (r = 0.98, p < 0.05, factor of 1.09). Linear PI and AUC(wash-in) had significantly earlier decreases after drug administration than video data (p = 0.015 and p = 0.03, respectively). The coefficient of variation was significantly lower when using video rather than linear data (p < 10(-4)). Conclusion: In conclusion, the use of linear data is the only mathematically valid methodology for determining a tumor's time-intensity curve and, in practice, it allows earlier demonstration of responses to antivascular drugs.